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On
Estimating Value-at-Risk Using Tail Index: An Application
to Indian Stock Market
-- G
P Samanta and Sanjay Kumar Thakur
In
this empirical study, the authors have assessed the accuracy
of the VaR estimates obtained through the application of tail-index.
The database consists of daily observations on two stock price
indices in India, viz., BSE Sensex, and BSE100 for the period
April 1, 1999 to March 31, 2005. The empirical results are
quite encouraging. It is seen that returns on both of these
index-portfolios do not follow a normal distribution. The
non-normality is triggered primarily due to the excess-kurtosis
problem, causing the underlying return distribution to have
a fatter tail than normal. In order to handle the fat tail,
the authors estimate the tail index, which measures the fatness
of the tails. The estimated tail index is then used to estimate
the Value-at-Risk (VaR). We observe that while normality assumption
for return distribution in most cases leads to the underestimation
of the VaR number, application of the Tail Index method improves
the VaR estimates. The accuracy of these estimates is checked
through the regulators' backtesting and Kupiec's tests. Results
show that tail index based methods provide relatively more
conservative VaR estimates and have a greater chance of passing
through the regulators' backtesting. However, one should be
careful while validating the VaR models, as the authors find
that the performance of a VaR model may be sensitive to the
sample size used in VaR estimation. Future research may extensively
address this issue and check the robustness of the results
across markets over a period of time.
©
2006 IUP . All Rights Reserved.
Time-varying
Volatility and Leverage Effect in Financial Markets of Asia-Pacific
Countries
-- Madhusudan Karmakar
This
paper investigates the dynamic behavior of stock returns of
ten market indices of Asia-Pacific countries, using symmetric
GARCH and Asymmetric TARCH models for a period of 11 years
from July 1994 to June 2005. The study finds an evidence of
time-varying volatility, which exhibits clustering, high persistence
and predictability for almost all the countries included in
the sample. In agreement with other studies, the author finds
the presence of a leverage effect for all markets where the
conditional variance is an asymmetric function of past innovation,
rising proportionately more during market declines. The findings
are useful to all market participants for pricing derivatives
and designing dynamic hedging strategies.
©
2006 IUP . All Rights Reserved.
An
Econometric Estimation of the Aggregate Import Demand Function
for India
-- Aruna Kumar Dash
This
study investigates the behavior of the aggregate import demand
function for India using the yearly time-series data and by
applying the Johansen Juselius multivariate cointegration
technique during 1970-2003 up to which the latest data is
available. In our empirical analysis of the aggregate import
demand function for India, cointegration and error correction
techniques have been used. Using macroeconomic variables such
as gross domestic product, unit value of import prices, prices
of domestically produced goods and foreign exchange reserves,
the empirical evidence suggests that there exists a cointegrating
relationship among these variables. Our econometric estimates
of the aggregate import demand function for India suggest
that import demand is dominated by GDP, when compared to the
unit value of import price, and foreign exchange reserves.
©
2006 IUP . All Rights Reserved.
An
Empirical Analysis of Stock Index
and its Future in India
--
Kailash
Chandra Pradhan and K Sham bhat
This
study examines the price discovery and causality between stock
index and its future in India. It investigates price discovery
and the causal nexus between S&P CNX Nifty and Nifty futures
for near-month, mid-month and far-month contracts separately.
The objectives of the study are investigated by employing
Johansen's cointegration test and the Vector Error Correction
Model (VECM). The daily closing data is taken from June 12,
2000 to February 24, 2005 for near-month, mid-month and far-month
contracts separately. All the required information for the
study has been retrieved from the National Stock Exchange
(NSE) website. The analysis reveals that spot leads futures,
and the spot market transfers the information to the futures
market.
©
2006 IUP . All Rights Reserved.
Does
Friday Repeat itself on Monday? An Analysis of the Day-of-the-Week
Effect on Autocorrelations of Stock Market Index Returns
-- K N Badhani, B D Kavidayal
and P C Kavidayal
The
most striking phenomenon among the stock market anomalies
is the interaction of autocorrelations and the day-of-the-week
effects. International evidences suggest that return autocorrelations
are the highest on weekends, i.e., between returns of Friday
and Monday. In this paper, differences in autocorrelations
of S&P CNX Nifty Index-returns across the different weekdays
have been investigated. The behavior of autocorrelations was
not only found varying according to the day-of-the-week, but
the positive and the negative returns were also showing different
patterns of autocorrelations. In conformity to the international
trend, the highest positive first-order autocorrelation was
observed at the weekend for Friday returns, but this weekend
effect was found significant for negative returns only. The
authors also observed significantly high negative second-order
autocorrelation for negative Monday returns. In both the cases,
the autocorrelations were found about seven times higher than
the average unconditional first-order and second-order autocorrelations,
respectively.
©
2006 IUP . All Rights Reserved.
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